Types of DATA! in Data Science
There are majorly 3 types of data we study in data science:
- Numerical Data
- Categorical Data
- Ordinal Data
Numerical Data:
Numerical data can also be classified in three categories as follows:
Discrete Data: Integer based values belongs to discrete data e.g. 200 units of smart phones (there cannot be 200.5 units of smartphones) so the certain amount of values are called discrete data.
Continuous Data: Continuous data can have any no. of possible values e.g. time taken by 100 people to complete a 100 meter race here time for 100 people could be (12.23 sec, 10.56 sec,………….) so the values are not integer these type of data belongs to continuous data.
Quantitative Measurement Data: Heights of people, stock prices these are the types of quantitative measurement data. Quantitative Measurement Data contains both discrete and continuous type of data.
Categorical Data:
Categorical Data is qualitative data that has not inherent mathematical meaning. e.g Colour, Gender, True/False, Yes/No (Binary data), State of residence etc.
Categorical data has no mathematical meaning it needs to be converted to numerical data to perform analysis on categorical data.
Ordinal Data:
Ordinal data is a mixture of both numerical and categorical data.
Categorical data that has mathematical meaning is termed as ordinal data e.g. Restaurant rating on scale of 1–5, ratings must be 1,2,3,4 or 5 but these values have mathematical meaning 1 means it’s a worse restaurant and 5 means it’s a best restaurant.
